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ZSI_Reconnect_China/WOS/.ipynb_checkpoints/wos_analyses_demo-checkpoin...

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{
"cells": [
{
"cell_type": "code",
"execution_count": 26,
"id": "40038234",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import janitor\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from matplotlib.ticker import MaxNLocator\n",
"import math\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "fb7baf32",
"metadata": {},
"outputs": [],
"source": [
"outdir=\"wos_processed_data\"\n",
"\n",
"wos = pd.read_excel(f\"{outdir}/wos_processed.xlsx\")\n",
"\n",
"wos_addresses = pd.read_excel(f\"{outdir}/wos_addresses.xlsx\")\n",
"\n",
"wos_affiliations = pd.read_excel(f\"{outdir}/wos_affiliations.xlsx\")\n",
"\n",
"wos_author_locations = pd.read_excel(f\"{outdir}/wos_author_locations.xlsx\")\n",
"\n",
"wos_univ_locations = pd.read_excel(f\"{outdir}/wos_univ_locations.xlsx\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "1e737dbf",
"metadata": {},
"outputs": [],
"source": [
"record_col = record_col=\"UT (Unique WOS ID)\""
]
},
{
"cell_type": "markdown",
"id": "a97f1cbb",
"metadata": {},
"source": [
"# Output - per yer, by Metrix taxonomy"
]
},
{
"cell_type": "markdown",
"id": "18e34c6b",
"metadata": {},
"source": [
"## Domains"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "af12584f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Domain_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Applied Sciences</td>\n",
" <td>5379</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Natural Sciences</td>\n",
" <td>1649</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Health Sciences</td>\n",
" <td>1106</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Economic &amp; Social Sciences</td>\n",
" <td>289</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Miscellaneous</td>\n",
" <td>156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Arts &amp; Humanities</td>\n",
" <td>13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Domain_English UT (Unique WOS ID)\n",
"0 Applied Sciences 5379\n",
"5 Natural Sciences 1649\n",
"3 Health Sciences 1106\n",
"2 Economic & Social Sciences 289\n",
"4 Miscellaneous 156\n",
"1 Arts & Humanities 13"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = 'Domain_English'\n",
"data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=record_col)\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "f8e72c87",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.barplot(data, x=record_col, y=group)\n",
"g.set_xlim(0,6000)\n",
"g.set_ylabel(\"Domain\")\n",
"for i in g.containers:\n",
" g.bar_label(i,)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "88742c07",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Publication Year</th>\n",
" <th>Domain_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>524</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>2022</td>\n",
" <td>Miscellaneous</td>\n",
" <td>41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63</th>\n",
" <td>2022</td>\n",
" <td>Health Sciences</td>\n",
" <td>368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62</th>\n",
" <td>2022</td>\n",
" <td>Economic &amp; Social Sciences</td>\n",
" <td>106</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>2022</td>\n",
" <td>Arts &amp; Humanities</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2012</td>\n",
" <td>Miscellaneous</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2012</td>\n",
" <td>Health Sciences</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2012</td>\n",
" <td>Economic &amp; Social Sciences</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2012</td>\n",
" <td>Arts &amp; Humanities</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>21</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>66 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Year Domain_English UT (Unique WOS ID)\n",
"65 2022 Natural Sciences 524\n",
"64 2022 Miscellaneous 41\n",
"63 2022 Health Sciences 368\n",
"62 2022 Economic & Social Sciences 106\n",
"61 2022 Arts & Humanities 4\n",
".. ... ... ...\n",
"4 2012 Miscellaneous 3\n",
"3 2012 Health Sciences 2\n",
"2 2012 Economic & Social Sciences 0\n",
"1 2012 Arts & Humanities 0\n",
"0 2012 Applied Sciences 21\n",
"\n",
"[66 rows x 3 columns]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = ['Publication Year','Domain_English']\n",
"data = wos.groupby(group)[record_col].nunique().unstack(fill_value=0).stack().reset_index().rename(columns={0:record_col}).sort_values(ascending=False, by=group+[record_col])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "151a7a8a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x173792047c0>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g=sns.lineplot(data.sort_values(ascending=True, by=group[-1]),y=record_col,x=group[0], hue=group[-1], marker=\"o\")\n",
"g.set(xticks=list(range(2012,2022+1,2)))\n",
"g.legend(title=None)"
]
},
{
"cell_type": "markdown",
"id": "dcae04bd",
"metadata": {},
"source": [
"## Field"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "d3807072",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Publication Year</th>\n",
" <th>Domain_English</th>\n",
" <th>Field_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>205</td>\n",
" </tr>\n",
" <tr>\n",
" <th>175</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Mathematics &amp; Statistics</td>\n",
" <td>61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>174</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Earth &amp; Environmental Sciences</td>\n",
" <td>134</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Chemistry</td>\n",
" <td>81</td>\n",
" </tr>\n",
" <tr>\n",
" <th>172</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Biology</td>\n",
" <td>43</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2012</td>\n",
" <td>Miscellaneous</td>\n",
" <td>Miscellaneous</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2012</td>\n",
" <td>Health Sciences</td>\n",
" <td>Clinical Medicine</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Information &amp; Communication Technologies</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Agriculture, Fisheries &amp; Forestry</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>177 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Year Domain_English \n",
"176 2022 Natural Sciences \\\n",
"175 2022 Natural Sciences \n",
"174 2022 Natural Sciences \n",
"173 2022 Natural Sciences \n",
"172 2022 Natural Sciences \n",
".. ... ... \n",
"4 2012 Miscellaneous \n",
"3 2012 Health Sciences \n",
"2 2012 Applied Sciences \n",
"1 2012 Applied Sciences \n",
"0 2012 Applied Sciences \n",
"\n",
" Field_English UT (Unique WOS ID) \n",
"176 Physics & Astronomy 205 \n",
"175 Mathematics & Statistics 61 \n",
"174 Earth & Environmental Sciences 134 \n",
"173 Chemistry 81 \n",
"172 Biology 43 \n",
".. ... ... \n",
"4 Miscellaneous 3 \n",
"3 Clinical Medicine 2 \n",
"2 Information & Communication Technologies 14 \n",
"1 Engineering 5 \n",
"0 Agriculture, Fisheries & Forestry 2 \n",
"\n",
"[177 rows x 4 columns]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = ['Publication Year',\"Domain_English\",'Field_English']\n",
"data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=group+[record_col])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "756513b5",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAjsAAAHHCAYAAABZbpmkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAADJ10lEQVR4nOzdeViUVfvA8e8M+46gCCgKLrggmrnvmiYuWabmkikuuYWWmZX+ssXyTVvUtNwyRTNtdancTQHNfcldEZXFBdzZYRhmnt8fxOQEKBgwA96f65rrdZ7lPPcz9DI357nPOSpFURSEEEIIIcoptakDEEIIIYQoSZLsCCGEEKJck2RHCCGEEOWaJDtCCCGEKNck2RFCCCFEuSbJjhBCCCHKNUl2hBBCCFGuSbIjhBBCiHJNkh0hhBBClGuS7AghypyOHTvSsWPHUr1meHg4KpWK8PDwUr2uEOK/k2RHiHJmxYoVqFQqbG1tuXbtWp79HTt2pEGDBo/U9sKFC1mxYsV/jLD0ZGVlMW/ePBo3boyzszOurq4EBAQwevRozp8/b+rwhBClxNLUAQghSoZGo2HWrFl8+eWXxdbmwoULqVixIsOGDSu2NktS37592bJlC4MGDWLUqFFotVrOnz/Pxo0bad26NXXr1i10W+3btycjIwNra+sSjFgIURIk2RGinHriiSdYunQpU6dOxdvb29ThFEhRFDIzM7GzsyvWdg8fPszGjRv53//+x//93/8Z7fvqq69ITEwsUntqtRpbW9tijFAIUVrkMZYQ5dT//d//odPpmDVr1kOPDQ0N5amnnsLDwwMbGxvq16/PokWLjI7x9fXlzJkzREREoFKpUKlUhrqZDz74AJVKlafd3EdqMTExRu0888wzbNu2jaZNm2JnZ8eSJUsKHUdhXbp0CYA2bdrk2WdhYYG7u7vRtmvXrjFy5Ei8vb2xsbHBz8+PcePGkZWVBRRcs3Pw4EG6deuGi4sL9vb2dOjQgb179xodk/v5XLx4kWHDhuHq6oqLiwvDhw8nPT09T3zfffcdzZs3x97engoVKtC+fXu2b99udMyWLVto164dDg4OODk50bNnT86cOWN0TEJCAsOHD6dq1arY2Njg5eXFc889Z/TzEOJxID07QpRTfn5+DB06lKVLlzJlypQH9u4sWrSIgIAAnn32WSwtLfn999955ZVX0Ov1hISEAPDFF18wYcIEHB0deeeddwCoXLnyI8UWGRnJoEGDGDNmDKNGjaJOnTqFjqOwqlevDsDq1atp06YNlpYF/7q7fv06zZs3JzExkdGjR1O3bl2uXbvGL7/8Qnp6eoGPrnbt2kX37t1p0qQJ77//Pmq12pCw7dmzh+bNmxsd379/f/z8/Jg5cybHjh3jm2++wcPDg08++cRwzPTp0/nggw9o3bo1H374IdbW1hw8eJBdu3bRtWtXAFatWkVwcDBBQUF88sknpKens2jRItq2bctff/2Fr68vkPMY78yZM0yYMAFfX19u3rzJjh07iIuLMxwjxGNBEUKUK6GhoQqgHD58WLl06ZJiaWmpvPrqq4b9HTp0UAICAozOSU9Pz9NOUFCQUqNGDaNtAQEBSocOHfIc+/777yv5/TrJjSU6OtqwrXr16gqgbN26Nc/xhY2jQ4cO+cZxP71er3To0EEBlMqVKyuDBg1SFixYoMTGxuY5dujQoYparVYOHz6cbzuKoihhYWEKoISFhRm2165dWwkKCjIck3sPfn5+ytNPP23Ylvv5jBgxwqjt559/XnF3dze8j4qKUtRqtfL8888rOp0u3zhSUlIUV1dXZdSoUUb7ExISFBcXF8P2e/fuKYDy2WefPfBzEuJxII+xhCjHatSowZAhQ/j666+Jj48v8Lj762WSkpK4ffs2HTp04PLlyyQlJRV7XH5+fgQFBZVoHCqVim3btjFjxgwqVKjA999/T0hICNWrV2fAgAGGmh29Xs+GDRvo1asXTZs2zbed/Bw/fpyoqChefPFF7ty5w+3bt7l9+zZpaWl07tyZ3bt3o9frjc4ZO3as0ft27dpx584dkpOTAdiwYQN6vZ733nsPtdr413NuHDt27CAxMZFBgwYZrnn79m0sLCxo0aIFYWFhQM5naW1tTXh4OPfu3SvSZydEeSPJjhDl3LRp08jOzn5g7c7evXvp0qULDg4OuLq6UqlSJUNRb0klO6URh42NDe+88w7nzp3j+vXrfP/997Rs2ZKffvqJ8ePHA3Dr1i2Sk5OLPBw/KioKgODgYCpVqmT0+uabb9BoNHlirlatmtH7ChUqABiSkUuXLqFWq6lfv/5Dr/vUU0/lue727du5efOm4d4/+eQTtmzZQuXKlWnfvj2ffvopCQkJRbpPIcoDqdkRopyrUaMGL730El9//TVTpkzJs//SpUt07tyZunXrMmfOHHx8fLC2tmbz5s3MnTs3T+9Efgrq/dDpdPluz2/kVXHE8SBeXl4MHDiQvn37EhAQwE8//fSf5gzKjeezzz7jiSeeyPcYR0dHo/cWFhb5HqcoSpGvu2rVKjw9PfPsv782aeLEifTq1YsNGzawbds23n33XWbOnMmuXbto3Lhxoa8pRFknyY4Qj4Fp06bx3XffGRXC5vr999/RaDT89ttvRj0PuY9D7ldQUpPbQ5GYmIirq6the2xsbKFjLEoc/4WVlRUNGzYkKiqK27dv4+HhgbOzM6dPny5SOzVr1gTA2dmZLl26FEtsNWvWRK/Xc/bs2QITqNzrenh4FOq6NWvW5I033uCNN94gKiqKJ554gtmzZ/Pdd98VS8xClAXyGEuIx0DNmjV56aWXWLJkSZ7HGLm9Dff3LiQlJREaGpqnHQcHh3znp8n9At69e7dhW1paGitXrix0jEWJozCioqKIi4vLsz0xMZH9+/dToUIFKlWqhFqtpnfv3vz+++8cOXIkz/EF9bo0adKEmjVr8vnnn5Oamppn/61bt4occ+/evVGr1Xz44Yd5erJy4wgKCsLZ2ZmPP/4YrVZb4HXT09PJzMw02lezZk2cnJzQaDRFjk2Iskx6doR4TLzzzjusWrWKyMhIAgICDNu7du2KtbU1vXr1YsyYMaSmprJ06VI8PDzyFDU3adKERYsWMWPGDGrVqoWHhwdPPfUUXbt2pVq1aowcOZI333wTCwsLli9fTqVKlfJNOPJTlDgK48SJE7z44ot0796ddu3a4ebmxrVr11i5ciXXr1/niy++MCRYH3/8Mdu3b6dDhw6MHj2aevXqER8fz88//8yff/5p1FuVS61W880339C9e3cCAgIYPnw4VapU4dq1a4SFheHs7Mzvv/9epJhr1arFO++8w0cffUS7du3o06cPNjY2HD58GG9vb2bOnImzszOLFi1iyJAhPPnkkwwcONDwOW/atIk2bdrw1VdfceHCBTp37kz//v2pX78+lpaWrF+/nhs3bjBw4MAif55ClGkmHQsmhCh29w89/7fg4GAFyDP0/LffflMaNmyo2NraKr6+vsonn3yiLF++PM+w8YSEBKVnz56Kk5OTAhgN/z569KjSokULxdraWqlWrZoyZ86cAoee9+zZM9/YCxtHYYae37hxQ5k1a5bSoUMHxcvLS7G0tFQqVKigPPXUU8ovv/yS5/jY2Fhl6NChSqVKlRQbGxulRo0aSkhIiKLRaBRFyTv0PNdff/2l9OnTR3F3d1dsbGyU6tWrK/3791d27txpOCZ36PmtW7eMzs3v81EURVm+fLnSuHFjxcbGRqlQoYLSoUMHZceOHUbHhIWFKUFBQYqLi4tia2ur1KxZUxk2bJhy5MgRRVEU5fbt20pISIhSt25dxcHBQXFxcVFatGih/PTTTw/83IQoj1SKUoTKOCGEEEKIMkZqdoQQQghRrkmyI4QQQohyTZIdIYQQQpRrkuwIIYQQolyTZEcIIYQQ5ZokO0IIIYQo12RSQXLWmrl+/TpOTk4FTocvhBBCCPOiKAopKSl4e3ujVhfcfyPJDnD9+nV8fHxMHYYQQgghHsGVK1eoWrVqgfsl2QGcnJyAnA/L2dnZxNEIIYQQojCSk5Px8fExfI8XRJId/ln
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for cat in sorted(data[group[-2]].unique()):\n",
" #data segment\n",
" sub_data = data[data[group[-2]]==cat]\n",
" sub_data = sub_data.complete({group[0]:range(int(data[group[0]].min()), int(data[group[0]].max()) + 1)}\n",
" ,group[-1],fill_value=0)\n",
" #plot\n",
" g=sns.lineplot(sub_data.sort_values(ascending=True, by=group[-1]),\n",
" y=record_col,x=group[0], hue=group[-1], marker=\"o\")\n",
" g.set(xticks=list(range(2012,2022+1,2)))\n",
" g.legend(title=None)\n",
" g.set_title(cat)\n",
" g.yaxis.set_major_locator(MaxNLocator(integer=True))\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"id": "09a6de71",
"metadata": {},
"source": [
"## SubField"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "0397eb85",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Publication Year</th>\n",
" <th>Domain_English</th>\n",
" <th>Field_English</th>\n",
" <th>SubField_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>774</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Optics</td>\n",
" <td>56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>773</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Nuclear &amp; Particle Physics</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>772</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Mathematical Physics</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>771</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>General Physics</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>770</th>\n",
" <td>2022</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Fluids &amp; Plasmas</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Information &amp; Communication Technologies</td>\n",
" <td>Artificial Intelligence &amp; Image Processing</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Mechanical Engineering &amp; Transports</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Industrial Engineering &amp; Automation</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Geological &amp; Geomatics Engineering</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2012</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Agriculture, Fisheries &amp; Forestry</td>\n",
" <td>Food Science</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>775 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Year Domain_English \n",
"774 2022 Natural Sciences \\\n",
"773 2022 Natural Sciences \n",
"772 2022 Natural Sciences \n",
"771 2022 Natural Sciences \n",
"770 2022 Natural Sciences \n",
".. ... ... \n",
"4 2012 Applied Sciences \n",
"3 2012 Applied Sciences \n",
"2 2012 Applied Sciences \n",
"1 2012 Applied Sciences \n",
"0 2012 Applied Sciences \n",
"\n",
" Field_English \n",
"774 Physics & Astronomy \\\n",
"773 Physics & Astronomy \n",
"772 Physics & Astronomy \n",
"771 Physics & Astronomy \n",
"770 Physics & Astronomy \n",
".. ... \n",
"4 Information & Communication Technologies \n",
"3 Engineering \n",
"2 Engineering \n",
"1 Engineering \n",
"0 Agriculture, Fisheries & Forestry \n",
"\n",
" SubField_English UT (Unique WOS ID) \n",
"774 Optics 56 \n",
"773 Nuclear & Particle Physics 28 \n",
"772 Mathematical Physics 2 \n",
"771 General Physics 14 \n",
"770 Fluids & Plasmas 21 \n",
".. ... ... \n",
"4 Artificial Intelligence & Image Processing 10 \n",
"3 Mechanical Engineering & Transports 1 \n",
"2 Industrial Engineering & Automation 3 \n",
"1 Geological & Geomatics Engineering 1 \n",
"0 Food Science 2 \n",
"\n",
"[775 rows x 5 columns]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = ['Publication Year',\"Domain_English\",'Field_English',\"SubField_English\"]\n",
"data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=group+[record_col])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "846596cf",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA8EAAAHHCAYAAACfjlo0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAADuEklEQVR4nOzdd3yN5//48dfJ3tNIEElI7FlbWjE/QalRs0pCxKaKFi21arRqK2olalOlqdqzhNpbkBBbjJBEJDLv3x/55XwdSUg4yUni/Xw8zqM9933d1/U+d85JvM+1VIqiKAghhBBCCCGEEB8APV0HIIQQQgghhBBC5BZJgoUQQgghhBBCfDAkCRZCCCGEEEII8cGQJFgIIYQQQgghxAdDkmAhhBBCCCGEEB8MSYKFEEIIIYQQQnwwJAkWQgghhBBCCPHBkCRYCCGEEEIIIcQHQ5JgIYQQQgghhBAfDEmChXhHLi4utGrVSmv13bx5E5VKRUBAgNbqFO9PpVIxfvz4LJV1cXHBx8cnR+PJaQcOHEClUnHgwAFdhyKEEEIIkSMkCRZ5XkBAACqVSv0wMTGhTJkyDBo0iIcPH+o6vA/Oy5cvGT16NC4uLpiZmVGuXDlGjBjxTnUdOHCA9u3b4+DggJGREUWKFKF169b8+eefWo5ae44cOcL48eOJjIzUdShqCQkJzJkzh+rVq2NlZYWNjQ0VK1akT58+XLlyRdfhCSGEEELkKQa6DkCIrJo4cSKurq68fPmSw4cPs3DhQrZt28bFixcxMzPTdXgfjJEjRzJ37lx69epFnTp1uHr1KqtWreKXX37JVj3jxo1j4sSJuLu707dvX5ydnYmIiGDbtm18/vnnrF69mi+++CKHXkXWxcXFYWDwf78qjxw5woQJE/Dx8cHGxkaj7NWrV9HTy/3vFj///HO2b99O165d8fPzIzExkStXrrB161bq169PuXLlslxXgwYNiIuLw8jIKAcjFkIIIYTQHUmCRb7RokULatasCUDv3r2xt7dn5syZ/PXXX3Tt2lXH0X041q1bR8uWLVm2bJn62JQpU7JVxx9//MHEiRPp0KEDa9aswdDQUH3um2++YefOnSQmJmot5vdhYmKS5bLGxsY5GEnGTpw4wdatW5k8eTLfffedxrn58+dnu8daT08vW69ZCCGEECK/keHQIt9q3LgxAGFhYQCEh4fTs2dPSpQogbGxMY6OjrRp04abN28C4O3tTaFChTJMrv73v/9RtmxZjWOrVq2idu3amJmZYWtrS4MGDdi1a1e6aw8fPkzt2rUxMTGhVKlS/P777+nK3Lhxg44dO2JnZ4eZmRl169bln3/+ydLr3LdvH5988gnm5ubY2NjQpk0bgoOD05U7cOAANWvWxMTEhNKlS/Pbb78xfvx4VCqVuoynpydVq1bNsJ2yZcvi5eX11nj09PRQFEXjWHaTv7Fjx2JnZ8fy5cs1EuA0Xl5eGvOtHz16hK+vL0WLFsXExISqVauyYsWKdNdFRETQvXt39ZBgb29vzp07l26utY+PDxYWFty7d4+2bdtiYWFB4cKFGTFiBMnJyRp1vjonePz48XzzzTcAuLq6qofop73HXp0TfPLkSVQqVYZx7ty5E5VKxdatW9XH7t27R69evShatCjGxsZUrFiR5cuXv/VeXr9+HQAPD4905/T19bG3t9c4du/ePXx9fSlWrBjGxsa4urrSv39/EhISgMznBB87dozmzZtjbW2NmZkZnp6eBAUFaZRJe7+Fhoaqe8qtra3p2bMnsbGx6eLLymds+/bt6ve/paUln376KZcuXdIo87bPvhBCCCHEqyQJFvlW2j/+0/6R//nnn7N582Z69uzJggULGDJkCM+fP+f27dsAdO/enYiICHbu3KlRT3h4OPv27ePLL79UH5swYQLdu3fH0NCQiRMnMmHCBJycnNi3b5/GtaGhoXTo0IFmzZoxY8YMbG1t8fHx0fhH+sOHD6lfvz47d+5kwIABTJ48mZcvX/LZZ5+xefPmN77GPXv24OXlxaNHjxg/fjzDhg3jyJEjeHh4aPwD/8yZMzRv3pyIiAgmTJiAr68vEydOZMuWLRr1de/enfPnz3Px4kWN4ydOnODatWsa9yAzPXv2ZMeOHWzfvv2tZTMSEhLClStXaNu2LZaWlm8tHxcXR8OGDVm5ciXdunVj+vTpWFtb4+Pjw5w5c9TlUlJSaN26NWvXrsXb25vJkyfz4MEDvL29M6w3OTkZLy8v7O3t+eWXX/D09GTGjBksXrw401jat2+vHnUwa9YsVq5cycqVKylcuHC6sjVr1qRUqVJs2LAh3bn169dja2ur/tLh4cOH1K1blz179jBo0CDmzJmDm5sbvr6+zJ49+433x9nZGYDVq1eTlJT0xrL379+ndu3arFu3js6dOzN37ly6d+/OwYMHM0xS0+zbt48GDRoQHR3NuHHjmDJlCpGRkTRu3Jjjx4+nK9+pUyeeP3/O1KlT6dSpEwEBAUyYMEGjTFY+YytXruTTTz/FwsKCn376ibFjx3L58mU+/vhjjff/2z77QgghhBAaFCHyOH9/fwVQ9uzZozx+/Fi5c+eOsm7dOsXe3l4xNTVV7t69qzx79kwBlOnTp2daT3JyslKiRAmlc+fOGsdnzpypqFQq5caNG4qiKEpISIiip6entGvXTklOTtYom5KSov5/Z2dnBVD+/fdf9bFHjx4pxsbGyvDhw9XHhg4dqgDKoUOH1MeeP3+uuLq6Ki4uLuo2wsLCFEDx9/dXl6tWrZpSpEgRJSIiQn3s3Llzip6entKjRw/1sdatWytmZmbKvXv31MdCQkIUAwMD5dWPeWRkpGJiYqKMHDlS43UNGTJEMTc3V2JiYjK9f4qiKImJicqXX36pGBkZKebm5sqRI0feWD4jf/31lwIos2bNylL52bNnK4CyatUq9bGEhASlXr16ioWFhRIdHa0oiqJs2rRJAZTZs2eryyUnJyuNGzdOd1+9vb0VQJk4caJGW9WrV1dq1KihcQxQxo0bp34+ffp0BVDCwsLSxers7Kx4e3urn48ePVoxNDRUnj59qj4WHx+v2NjYKL169VIf8/X1VRwdHZUnT55o1NelSxfF2tpaiY2NzfT+pKSkKJ6engqgFC1aVOnatavy66+/Krdu3UpXtkePHoqenp5y4sSJDOtRFEXZv3+/Aij79+9XH3d3d1e8vLw03v+xsbGKq6ur0qxZM/WxcePGKYDGa1MURWnXrp1ib2+vfp6Vz9jz588VGxsbxc/PT+N8eHi4Ym1trT6elc++EEIIIcSrpCdY5BtNmzalcOHCODk50aVLFywsLNi8eTPFixfH1NQUIyMjDhw4wLNnzzK8Xk9Pj27duhEYGMjz58/Vx1evXk39+vVxdXUFYMuWLaSkpPDDDz+kW+To1aHFABUqVOCTTz5RPy9cuDBly5blxo0b6mPbtm2jdu3afPzxx+pjFhYW9OnTh5s3b3L58uUM433w4AFnz57Fx8cHOzs79fEqVarQrFkztm3bBqT2aO7Zs4e2bdtSrFgxdTk3NzdatGihUae1tTVt2rRh7dq16iHNycnJrF+/nrZt22Jubp5hLGm+/fZbtm/fzoULF6hTpw4tW7bk7NmzGjGrVCqN+cKvi46OBshSLzCk3j8HBweNed+GhoYMGTKEmJgYDh48CMCOHTswNDTEz89PXU5PT4+BAwdmWne/fv00nn/yyScaP7v31blzZxITEzVWu961axeRkZF07twZAEVR2LRpE61bt0ZRFJ48eaJ+eHl5ERUVxenTpzNtQ6VSsXPnTn788UdsbW1Zu3YtAwcOxNnZmc6dO6vnBKekpLBlyxZat26tnlv/ej0ZOXv2LCEhIXzxxRdERESoY3vx4gVNmjTh33//JSUlReOajO5rRESE+meflc/Y7t27iYyMpGvXrhr3RF9fnzp16rB//36ALH32hRBCCCFeJUmwyDd+/fVXdu/ezf79+7l8+TI3btxQDyc1Njbmp59+Yvv27RQtWpQGDRrw888/Ex4erlFHjx49iIuLUw9Dvnr1KqdOnaJ79+7qMtevX0dPT48
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for cat in sorted(data[group[-2]].unique()):\n",
" sub_data = data[data[group[-2]]==cat]\n",
" sub_data = sub_data.complete({group[0]:range(int(data[group[0]].min()), int(data[group[0]].max()) + 1)}\n",
" ,group[-1],fill_value=0)\n",
" g=sns.lineplot(sub_data.sort_values(ascending=True, by=group[-1]),y=record_col,x=group[0],\n",
" hue=group[-1], marker=\"o\")\n",
" g.set(xticks=list(range(2012,2022+1,2)))\n",
" g.legend(title=None,bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0., ncols=math.ceil(len(g.legend_.texts)/12))\n",
" g.set_title(cat)\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"id": "91d2cc8a",
"metadata": {},
"source": [
"## Collabs "
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "f6dfe4d0",
"metadata": {},
"outputs": [],
"source": [
"wos_collabs = wos_addresses[wos_addresses[\"Country_Type\"]!=\"Other\"][[record_col,\"Country\"]].drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "b3adb06a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Country</th>\n",
" <th>count</th>\n",
" <th>percent</th>\n",
" <th>weight</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Germany</td>\n",
" <td>2309</td>\n",
" <td>0.233492</td>\n",
" <td>0.101095</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>France</td>\n",
" <td>1632</td>\n",
" <td>0.165032</td>\n",
" <td>0.071454</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Italy</td>\n",
" <td>1260</td>\n",
" <td>0.127414</td>\n",
" <td>0.055166</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Netherlands</td>\n",
" <td>1063</td>\n",
" <td>0.107493</td>\n",
" <td>0.046541</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Spain</td>\n",
" <td>987</td>\n",
" <td>0.099808</td>\n",
" <td>0.043214</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Sweden</td>\n",
" <td>832</td>\n",
" <td>0.084134</td>\n",
" <td>0.036427</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Finland</td>\n",
" <td>700</td>\n",
" <td>0.070786</td>\n",
" <td>0.030648</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Denmark</td>\n",
" <td>566</td>\n",
" <td>0.057235</td>\n",
" <td>0.024781</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Ireland</td>\n",
" <td>552</td>\n",
" <td>0.055820</td>\n",
" <td>0.024168</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Belgium</td>\n",
" <td>499</td>\n",
" <td>0.050460</td>\n",
" <td>0.021848</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Poland</td>\n",
" <td>486</td>\n",
" <td>0.049146</td>\n",
" <td>0.021278</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Austria</td>\n",
" <td>373</td>\n",
" <td>0.037719</td>\n",
" <td>0.016331</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Portugal</td>\n",
" <td>365</td>\n",
" <td>0.036910</td>\n",
" <td>0.015981</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Greece</td>\n",
" <td>320</td>\n",
" <td>0.032359</td>\n",
" <td>0.014011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Hungary</td>\n",
" <td>181</td>\n",
" <td>0.018303</td>\n",
" <td>0.007925</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Czech Republic</td>\n",
" <td>144</td>\n",
" <td>0.014562</td>\n",
" <td>0.006305</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Romania</td>\n",
" <td>133</td>\n",
" <td>0.013449</td>\n",
" <td>0.005823</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Slovenia</td>\n",
" <td>111</td>\n",
" <td>0.011225</td>\n",
" <td>0.004860</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Slovakia</td>\n",
" <td>75</td>\n",
" <td>0.007584</td>\n",
" <td>0.003284</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Lithuania</td>\n",
" <td>68</td>\n",
" <td>0.006876</td>\n",
" <td>0.002977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>Estonia</td>\n",
" <td>65</td>\n",
" <td>0.006573</td>\n",
" <td>0.002846</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>Luxembourg</td>\n",
" <td>59</td>\n",
" <td>0.005966</td>\n",
" <td>0.002583</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>Croatia</td>\n",
" <td>56</td>\n",
" <td>0.005663</td>\n",
" <td>0.002452</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>Bulgaria</td>\n",
" <td>48</td>\n",
" <td>0.004854</td>\n",
" <td>0.002102</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>Cyprus</td>\n",
" <td>35</td>\n",
" <td>0.003539</td>\n",
" <td>0.001532</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>Latvia</td>\n",
" <td>20</td>\n",
" <td>0.002022</td>\n",
" <td>0.000876</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Malta</td>\n",
" <td>13</td>\n",
" <td>0.001315</td>\n",
" <td>0.000569</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Country count percent weight\n",
"0 Germany 2309 0.233492 0.101095\n",
"1 France 1632 0.165032 0.071454\n",
"2 Italy 1260 0.127414 0.055166\n",
"3 Netherlands 1063 0.107493 0.046541\n",
"4 Spain 987 0.099808 0.043214\n",
"5 Sweden 832 0.084134 0.036427\n",
"6 Finland 700 0.070786 0.030648\n",
"7 Denmark 566 0.057235 0.024781\n",
"8 Ireland 552 0.055820 0.024168\n",
"9 Belgium 499 0.050460 0.021848\n",
"10 Poland 486 0.049146 0.021278\n",
"11 Austria 373 0.037719 0.016331\n",
"12 Portugal 365 0.036910 0.015981\n",
"13 Greece 320 0.032359 0.014011\n",
"14 Hungary 181 0.018303 0.007925\n",
"15 Czech Republic 144 0.014562 0.006305\n",
"16 Romania 133 0.013449 0.005823\n",
"17 Slovenia 111 0.011225 0.004860\n",
"18 Slovakia 75 0.007584 0.003284\n",
"19 Lithuania 68 0.006876 0.002977\n",
"20 Estonia 65 0.006573 0.002846\n",
"21 Luxembourg 59 0.005966 0.002583\n",
"22 Croatia 56 0.005663 0.002452\n",
"23 Bulgaria 48 0.004854 0.002102\n",
"24 Cyprus 35 0.003539 0.001532\n",
"25 Latvia 20 0.002022 0.000876\n",
"26 Malta 13 0.001315 0.000569"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"collab_desc = wos_collabs[wos_collabs[\"Country\"]!=\"China\"][\"Country\"].value_counts().reset_index()\n",
"collab_desc[\"percent\"] = collab_desc[\"count\"]/wos_collabs[record_col].nunique()\n",
"collab_desc[\"weight\"] = collab_desc[\"count\"]/wos_collabs[record_col].size\n",
"collab_desc"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "140395ac",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" <th>Affiliations</th>\n",
" <th>Affiliations_merged</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>BULGARIAN ACADEMY OF SCIENCES</td>\n",
" <td>BULGARIAN ACADEMY OF SCIENCES</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>WOS:000297893800037</td>\n",
" <td>BEIJING INSTITUTE OF TECHNOLOGY</td>\n",
" <td>BEIJING INSTITUTE OF TECHNOLOGY</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>WOS:000297893800037</td>\n",
" <td>UNIVERSIDAD POLITECNICA DE MADRID</td>\n",
" <td>UNIVERSIDAD POLITECNICA DE MADRID</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>WOS:000301090100061</td>\n",
" <td>UNIVERSITY OF LUBECK</td>\n",
" <td>UNIVERSITY OF LUBECK</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63585</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>HUZHOU UNIVERSITY</td>\n",
" <td>HUZHOU UNIVERSITY</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63586</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>SHANGHAITECH UNIVERSITY</td>\n",
" <td>SHANGHAITECH UNIVERSITY</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63587</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>SHANGHAI OCEAN UNIVERSITY</td>\n",
" <td>SHANGHAI UNIVERSITY</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63588</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>SHANGHAI JIAO TONG UNIVERSITY</td>\n",
" <td>SHANGHAI UNIVERSITY</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63589</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>UNIVERSITAT POLITECNICA DE VALENCIA</td>\n",
" <td>UNIVERSITAT POLITECNICA DE VALENCIA</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>63590 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" UT (Unique WOS ID) Affiliations \n",
"0 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \\\n",
"1 WOS:000209536100003 BULGARIAN ACADEMY OF SCIENCES \n",
"2 WOS:000297893800037 BEIJING INSTITUTE OF TECHNOLOGY \n",
"3 WOS:000297893800037 UNIVERSIDAD POLITECNICA DE MADRID \n",
"4 WOS:000301090100061 UNIVERSITY OF LUBECK \n",
"... ... ... \n",
"63585 WOS:000947693400001 HUZHOU UNIVERSITY \n",
"63586 WOS:000947693400001 SHANGHAITECH UNIVERSITY \n",
"63587 WOS:000947693400001 SHANGHAI OCEAN UNIVERSITY \n",
"63588 WOS:000947693400001 SHANGHAI JIAO TONG UNIVERSITY \n",
"63589 WOS:000947693400001 UNIVERSITAT POLITECNICA DE VALENCIA \n",
"\n",
" Affiliations_merged \n",
"0 NATURAL HISTORY MUSEUM LONDON \n",
"1 BULGARIAN ACADEMY OF SCIENCES \n",
"2 BEIJING INSTITUTE OF TECHNOLOGY \n",
"3 UNIVERSIDAD POLITECNICA DE MADRID \n",
"4 UNIVERSITY OF LUBECK \n",
"... ... \n",
"63585 HUZHOU UNIVERSITY \n",
"63586 SHANGHAITECH UNIVERSITY \n",
"63587 SHANGHAI UNIVERSITY \n",
"63588 SHANGHAI UNIVERSITY \n",
"63589 UNIVERSITAT POLITECNICA DE VALENCIA \n",
"\n",
"[63590 rows x 3 columns]"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos_affiliations"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "df1f03ea",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Publication Type', 'Authors', 'Book Authors', 'Book Editors',\n",
" 'Book Group Authors', 'Author Full Names', 'Book Author Full Names',\n",
" 'Group Authors', 'Article Title', 'Source Title', 'Book Series Title',\n",
" 'Book Series Subtitle', 'Language', 'Document Type', 'Conference Title',\n",
" 'Conference Date', 'Conference Location', 'Conference Sponsor',\n",
" 'Conference Host', 'Author Keywords', 'Keywords Plus', 'Abstract',\n",
" 'Addresses', 'Affiliations', 'Reprint Addresses', 'Email Addresses',\n",
" 'Researcher Ids', 'ORCIDs', 'Funding Orgs', 'Funding Name Preferred',\n",
" 'Funding Text', 'Cited References', 'Cited Reference Count',\n",
" 'Times Cited, WoS Core', 'Times Cited, All Databases',\n",
" '180 Day Usage Count', 'Since 2013 Usage Count', 'Publisher',\n",
" 'Publisher City', 'Publisher Address', 'ISSN', 'eISSN', 'ISBN',\n",
" 'Journal Abbreviation', 'Journal ISO Abbreviation', 'Publication Date',\n",
" 'Publication Year', 'Volume', 'Issue', 'Part Number', 'Supplement',\n",
" 'Special Issue', 'Meeting Abstract', 'Start Page', 'End Page',\n",
" 'Article Number', 'DOI', 'DOI Link', 'Book DOI', 'Early Access Date',\n",
" 'Number of Pages', 'WoS Categories', 'Web of Science Index',\n",
" 'Research Areas', 'IDS Number', 'Pubmed Id', 'Open Access Designations',\n",
" 'Highly Cited Status', 'Hot Paper Status', 'Date of Export',\n",
" 'UT (Unique WOS ID)', 'Web of Science Record', 'issn_var', 'issn',\n",
" 'Domain_English', 'Field_English', 'SubField_English', '2.00 SEQ',\n",
" 'Source_title', 'srcid', 'issn_type'],\n",
" dtype='object')"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos.columns"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "e4c50e14",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Affiliations</th>\n",
" <th>Addresses</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>University of Trento; University of Oviedo; Ts...</td>\n",
" <td>[Salucci, Marco] Univ Trento, DICAM Dept Civil...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Peking University; University of Hamburg; Univ...</td>\n",
" <td>[Huang, Yu; Fu, Zuntao] Peking Univ, Sch Phys,...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Southeast University - China; University of Ca...</td>\n",
" <td>[Feng, De-Cheng] Southeast Univ, Minist Educ, ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Ocean University of China; Universidade de Lis...</td>\n",
" <td>[Zhao, Yuliang; Dong, Sheng; Jiang, Fengyuan] ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Beihang University; Ministry of Natural Resour...</td>\n",
" <td>[Li, Xiaohui; Yang, Dongkai] Beihang Univ, Sch...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8587</th>\n",
" <td>Shanghai Ocean University; Ministry of Natural...</td>\n",
" <td>[He, Qi; Zha, Cheng; Song, Wei; Du, Yanling] S...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8588</th>\n",
" <td>Nanjing Audit University; WSB University</td>\n",
" <td>[Hasan, Md Morshadul] Nanjing Audit Univ, Sch ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8589</th>\n",
" <td>China University of Mining &amp; Technology; Delft...</td>\n",
" <td>[Li, Yong; Cheng, Gang; Kuai, Moshen] China Un...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8590</th>\n",
" <td>Nanjing University of Information Science &amp; Te...</td>\n",
" <td>[Zeng, Rong; Zhang, Jiapeng] Nanjing Univ Info...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8591</th>\n",
" <td>Nanjing University of Posts &amp; Telecommunicatio...</td>\n",
" <td>[Jia, Yan; Gao, Yun; Tang, Jing; Chen, Yixiang...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8592 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" Affiliations \n",
"0 University of Trento; University of Oviedo; Ts... \\\n",
"1 Peking University; University of Hamburg; Univ... \n",
"2 Southeast University - China; University of Ca... \n",
"3 Ocean University of China; Universidade de Lis... \n",
"4 Beihang University; Ministry of Natural Resour... \n",
"... ... \n",
"8587 Shanghai Ocean University; Ministry of Natural... \n",
"8588 Nanjing Audit University; WSB University \n",
"8589 China University of Mining & Technology; Delft... \n",
"8590 Nanjing University of Information Science & Te... \n",
"8591 Nanjing University of Posts & Telecommunicatio... \n",
"\n",
" Addresses \n",
"0 [Salucci, Marco] Univ Trento, DICAM Dept Civil... \n",
"1 [Huang, Yu; Fu, Zuntao] Peking Univ, Sch Phys,... \n",
"2 [Feng, De-Cheng] Southeast Univ, Minist Educ, ... \n",
"3 [Zhao, Yuliang; Dong, Sheng; Jiang, Fengyuan] ... \n",
"4 [Li, Xiaohui; Yang, Dongkai] Beihang Univ, Sch... \n",
"... ... \n",
"8587 [He, Qi; Zha, Cheng; Song, Wei; Du, Yanling] S... \n",
"8588 [Hasan, Md Morshadul] Nanjing Audit Univ, Sch ... \n",
"8589 [Li, Yong; Cheng, Gang; Kuai, Moshen] China Un... \n",
"8590 [Zeng, Rong; Zhang, Jiapeng] Nanjing Univ Info... \n",
"8591 [Jia, Yan; Gao, Yun; Tang, Jing; Chen, Yixiang... \n",
"\n",
"[8592 rows x 2 columns]"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos[[\"Affiliations\",\"Addresses\"]]"
]
}
],
"metadata": {
"kernelspec": {
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